End of training

README.md

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+---
+library_name: peft
+license: apache-2.0
+base_model: JackFram/llama-160m
+tags:
+- axolotl
+- generated_from_trainer
+model-index:
+- name: 826671fb-74bf-4adf-893c-6be73c4cb670
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
+<details><summary>See axolotl config</summary>
+
+axolotl version: `0.4.1`
+```yaml
+adapter: lora
+base_model: JackFram/llama-160m
+bf16: true
+chat_template: llama3
+dataset_prepared_path: null
+datasets:
+- data_files:
+  - 74abca5b35871829_train_data.json
+  ds_type: json
+  format: custom
+  path: /workspace/input_data/74abca5b35871829_train_data.json
+  type:
+    field_instruction: chat
+    field_output: system
+    format: '{instruction}'
+    no_input_format: '{instruction}'
+    system_format: '{system}'
+    system_prompt: ''
+debug: null
+device_map:
+  ? ''
+  : 0,1,2,3,4,5,6,7
+early_stopping_patience: 2
+eval_max_new_tokens: 128
+eval_steps: 100
+eval_table_size: null
+flash_attention: true
+gradient_accumulation_steps: 8
+gradient_checkpointing: true
+group_by_length: false
+hub_model_id: Alphatao/826671fb-74bf-4adf-893c-6be73c4cb670
+hub_repo: null
+hub_strategy: null
+hub_token: null
+learning_rate: 0.0002
+load_best_model_at_end: true
+load_in_4bit: false
+load_in_8bit: false
+local_rank: null
+logging_steps: 1
+lora_alpha: 32
+lora_dropout: 0.05
+lora_fan_in_fan_out: null
+lora_model_dir: null
+lora_r: 16
+lora_target_linear: true
+lora_target_modules:
+- q_proj
+- k_proj
+- v_proj
+- o_proj
+- down_proj
+- up_proj
+lr_scheduler: cosine
+max_grad_norm: 1.0
+max_steps: 12977
+micro_batch_size: 4
+mlflow_experiment_name: /tmp/74abca5b35871829_train_data.json
+model_type: AutoModelForCausalLM
+num_epochs: 2
+optimizer: adamw_bnb_8bit
+output_dir: miner_id_24
+pad_to_sequence_len: true
+resume_from_checkpoint: null
+s2_attention: null
+sample_packing: false
+save_steps: 100
+sequence_len: 2048
+special_tokens:
+  pad_token: </s>
+strict: false
+tf32: true
+tokenizer_type: AutoTokenizer
+train_on_inputs: false
+trust_remote_code: true
+val_set_size: 0.04457917261055635
+wandb_entity: null
+wandb_mode: online
+wandb_name: 029def98-2bf0-4673-93ae-3a488c6daa7a
+wandb_project: Gradients-On-Demand
+wandb_run: your_name
+wandb_runid: 029def98-2bf0-4673-93ae-3a488c6daa7a
+warmup_steps: 10
+weight_decay: 0.0
+xformers_attention: null
+
+```
+
+</details><br>
+
+# 826671fb-74bf-4adf-893c-6be73c4cb670
+
+This model is a fine-tuned version of [JackFram/llama-160m](https://huggingface.co/JackFram/llama-160m) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0007
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 32
+- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- training_steps: 6698
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.5646        | 0.0003 | 1    | 2.5999          |
+| 0.0154        | 0.0299 | 100  | 0.0136          |
+| 0.0037        | 0.0597 | 200  | 0.0048          |
+| 0.0026        | 0.0896 | 300  | 0.0036          |
+| 0.0022        | 0.1194 | 400  | 0.0021          |
+| 0.0017        | 0.1493 | 500  | 0.0023          |
+| 0.0022        | 0.1792 | 600  | 0.0010          |
+| 0.0008        | 0.2090 | 700  | 0.0019          |
+| 0.0003        | 0.2389 | 800  | 0.0008          |
+| 0.0006        | 0.2688 | 900  | 0.0008          |
+| 0.0002        | 0.2986 | 1000 | 0.0008          |
+| 0.0002        | 0.3285 | 1100 | 0.0007          |
+| 0.0004        | 0.3583 | 1200 | 0.0008          |
+| 0.0005        | 0.3882 | 1300 | 0.0007          |
+
+
+### Framework versions
+
+- PEFT 0.13.2
+- Transformers 4.46.0
+- Pytorch 2.5.0+cu124
+- Datasets 3.0.1
+- Tokenizers 0.20.1

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